class_docstr: A posterior based on a PyTorch Distribution.
  
  NOTE: For any attribute that is not explicitly defined on the Posterior level, this
  returns the corresponding attribute of the distribution. This allows easy access
  to the distribution attributes, without having to expose them on the Posterior.
class_docstr_tok: ["A","posterior","based","on","a","PyTorch","Distribution",".","NOTE",":","For","any","attribute","that","is","not","explicitly","defined","on","the","Posterior","level",",","this","returns","the","corresponding","attribute","of","the","distribution",".","This","allows","easy","access","to","the","distribution","attributes",",","without","having","to","expose","them","on","the","Posterior","."]
docstr: A minimal utility to support pickle protocol.
docstr_tok: ["A","minimal","utility","to","support","pickle","protocol","."]
code: def __setstate__(self, d: Dict[str, Any]) -> None:
      r"""A minimal utility to support pickle protocol."""
      self.__dict__ = d
  
file_path: botorch/botorch/posteriors/torch.py
imports: from __future__ import annotations
  from typing import Any, Dict, Optional
  import torch
  from botorch.posteriors.posterior import Posterior
  from torch import Tensor
  from torch.distributions.distribution import Distribution
label_desc: Use image node_id 7 for calling the TorchPosterior obj's underlying member method code with example usage: obj.__setstate__(d) without return types